AI / ML Engineer

Kimber Limited; Dublin; Remote; EUR 70,000 - 110,000; Full time

Job summary

Kimber Limited is seeking an AI/ML Engineer to design, build, and deploy intelligent systems at the heart of client platforms, from data preparation to production.

You will focus on real-world AI that is measurable, observable, and reliable, working with full-stack and platform engineers to integrate models into client applications.

Qualifications

• 3+ years building and shipping ML/AI systems.
• Strong Python skills and ML/data tooling.
• Hands-on experience with LLM APIs, embeddings, and vector search.
• Understanding of model evaluation, data quality, and production monitoring.
• Ability to explain technical trade-offs clearly to non-specialist stakeholders.

Responsibilities

• Design and build ML and LLM-powered pipelines from data prep to deployment.
• Develop retrieval-augmented generation, agent, and workflow systems.
• Define evaluation methods and monitor quality, cost, and latency in production.
• Collaborate with full-stack and platform engineers to integrate models into client apps.
• Advise clients on where AI creates real value and where simpler approaches are better.

Skills

Python

ML pipelines

Production monitoring

Model evaluation

Stakeholder communication

Tools

LLM APIs

Vector search

Embeddings

MLOps tooling

Job description

Design and deploy machine learning pipelines for real-world enterprise applications.

• Full-time
• Dublin / Remote

About the role

As an AI / ML Engineer you will design, build, and deploy the intelligent systems at the heart of our client platforms, from retrieval and agent workflows to predictive models running in production.

You will focus on AI that holds up in the real world: measurable, observable, and reliable, not just impressive in a demo.

What you'll do

• Design and build machine learning and LLM-powered pipelines, from data preparation to deployment.
• Develop retrieval-augmented generation (RAG), agent, and workflow automation systems.
• Define evaluation approaches and monitor model quality, cost, and latency in production.
• Work with full-stack and platform engineers to integrate models into client applications.
• Advise clients on where AI creates real value and where simpler approaches are better.

What you'll bring

• 3+ years of experience building and shipping machine learning or AI systems.
• Strong Python skills and experience with common ML and data tooling.
• Hands-on experience with LLM APIs, embeddings, and vector search.
• Understanding of model evaluation, data quality, and production monitoring.
• Ability to explain technical trade-offs clearly to non-specialist stakeholders.

Nice to have

• Experience with MLOps tooling and model serving on a major cloud provider.
• Experience fine-tuning models or working with synthetic data strategies.
• Awareness of GDPR and responsible AI practices.